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Answer:
Se=1.2
Step-by-step explanation:
The standard error is the standard deviation of a sample population. "It measures the accuracy with which a sample represents a population".
The central limit theorem (CLT) states "that the distribution of sample means approximates a normal distribution, as the sample size becomes larger, assuming that all samples are identical in size, and regardless of the population distribution shape"
The sample mean is defined as:
And the distribution for the sample mean is given by:
Let X denotes the random variable that measures the particular characteristic of interest. Let, X1, X2, …, Xn be the values of the random variable for the n units of the sample.
As the sample size is large,(>30) it can be assumed that the distribution is normal. The standard error of the sample mean X bar is given by:
If we replace the values given we have:
So then the distribution for the sample mean is:
Answer:
probability that Shaun loses both games
Step-by-step explanation:
Games are independent, so we find each separate probability, and multiply them.
In a chess club the probability that Shaun will beat Mike is 3/8.
So probability that Shaun loses.
The probability that Shaun will beat Tim is 5/7 .
So probability that Shaun loses.
What is the probability that Shaun loses both games?
This is:
probability that Shaun loses both games